library(Seurat)
## Loading required package: ggplot2
## Loading required package: cowplot
##
## Attaching package: 'cowplot'
## The following object is masked from 'package:ggplot2':
##
## ggsave
## Loading required package: Matrix
all10x <- readRDS('/projects/pytrik/sc_adipose/analyze_10x_fluidigm/data/10x')
markers <- read.table('/projects/pytrik/sc_adipose/analyze_10x_fluidigm/data/markergenes/markergenes-cluster12-negbinom.txt', header=T)
Violin plots
VlnPlot(all10x, features.plot=as.vector(markers[,'gene'][1:100]), group.by='res.0.5', point.size.use=-1, nCol=2, x.lab.rot=T, size.x.use=10)
Average expressions
mixcluster_vs_rest <- unlist(lapply(all10x@meta.data$res.0.5, function(x){
if (x == '12'){
return('mixcluster')
} else {
return('rest')
}
}))
all10x@meta.data['mixcluster'] <- mixcluster_vs_rest
avg_expr <- AverageExpression(SetAllIdent(all10x, 'mixcluster'), genes.use=as.vector(markers[,'gene'][1:100]))
## Finished averaging RNA for cluster mixcluster
## Finished averaging RNA for cluster rest
print(avg_expr)
## mixcluster rest
## RAB13 11.4056217 2.2719939
## DYNC1LI2 2.9724448 0.6170730
## ACTB 107.9807152 28.7649360
## MAP1B 18.5016560 6.5312128
## ANXA2 48.3992075 15.4001891
## LDHA 23.7716134 7.3628231
## SNRPD2 7.6243154 2.6096194
## SKP1 10.8256393 3.7018511
## ATP5B 5.4731719 1.8152643
## PGK1 5.3340770 1.7155981
## PRDX1 14.4368723 4.7837915
## MYL12B 16.5824283 5.6989478
## TPM2 34.4436601 10.3015765
## VDAC1 5.6399890 2.0459610
## NQO1 9.2374137 3.1992011
## LDHB 9.0845190 3.2006484
## PPIA 24.5699183 9.9131921
## MDH1 2.2645885 0.7279586
## ANXA5 13.9581479 5.4019235
## MYL12A 19.3939996 6.9472637
## KIF1C 1.1580022 0.4042845
## ANXA1 11.7331312 4.0801157
## ARF4 6.3156630 2.3873689
## MAP4 4.2691385 1.6612717
## ANP32B 7.3917211 3.0901031
## PALLD 3.2582446 1.1595520
## CCND1 12.8155896 4.2152080
## PPP1R7 1.3771064 0.4559037
## ANXA4 0.9910171 0.3119008
## PSMC1 1.8565817 0.6670085
## RPL22 18.0802385 13.6614206
## CHMP5 2.2475471 0.8133687
## TRAK2 0.6266629 0.2023215
## TSR2 0.7283677 0.2514674
## CCT8 2.7170538 1.0197912
## TALDO1 4.1011196 1.4744413
## PKM 11.2169466 4.5918950
## TCEAL4 3.1529698 1.2502213
## GLRX3 2.7711079 1.0939891
## NPM1 23.0252024 9.4687059
## GSTO1 6.4090672 2.6387276
## RPL38 19.6448397 15.0090821
## RHOA 11.7100164 5.2632229
## ACTG1 58.3299147 24.2284448
## TPM1 48.2247502 19.5171008
## ETFA 1.4864417 0.6067108
## PINK1 0.8864088 0.3485708
## GLO1 2.1721765 0.8808620
## SDHC 2.8869098 1.1868481
## CALM2 14.6674950 11.1754578
## SDCBP 1.9522782 0.7591412
## ACOT7 1.0220068 0.3728179
## XRCC6 2.4669845 0.9961482
## ARPC3 8.9488207 3.8317064
## MOCS2 1.6057052 0.6131904
## COX8A 9.5675354 7.0774526
## CCT7 2.1654347 0.8407693
## PSME1 1.4480834 0.5684054
## ANXA6 1.8662255 0.6990283
## COPS6 2.9099862 1.1948019
## GAPDH 78.6747297 35.5773008
## HNRNPH3 2.5323273 1.0065451
## CSRP1 4.4190642 1.7509797
## COPS8 1.6976593 0.6760533
## ALDOA 15.4232089 6.8643521
## HINT1 15.6863038 11.2673292
## FAU 19.6744245 14.0563802
## ARPC4 2.9015761 1.2551251
## GHITM 3.0328364 1.2742042
## SCP2 2.2556397 0.9569698
## PSMB3 4.0481388 1.6106892
## TCEB2 10.1717989 7.4572456
## NDUFB6 2.6537542 1.1506787
## UQCRC2 1.3804937 0.5331099
## PRPS1 1.3683550 0.4798471
## ATP5H 5.4960878 2.3390760
## HTATSF1 1.1708382 0.4638847
## VBP1 1.6022892 0.6386328
## ENO1 14.8790232 6.7066811
## CRYAB 18.9404799 7.3762204
## YWHAQ 6.4686375 2.9145156
## PSMC3IP 0.8877453 0.3202799
## ZEB1 1.5141888 0.5936900
## MINOS1 3.9176994 2.8091867
## RPS26 14.6821112 10.8973177
## EIF4A1 11.3225181 4.8392496
## PSMC4 1.2766637 0.4702430
## HADHB 0.9749347 0.3807320
## PSMD2 3.6985492 1.5547875
## TMSB10 153.4991029 113.1099784
## KIF5B 4.7131726 2.1322704
## UQCRH 9.6206952 6.8209649
## CMPK1 2.1472764 0.8930390
## ARL1 1.4842055 0.5912341
## EIF3I 4.0479870 1.7472347
## EDF1 7.3976771 5.2080483
## S100A11 43.0101188 18.9626109
## PRDX6 5.9363655 2.5672280
## ESD 2.3907364 0.9864991
## HNRNPA3 4.9709106 2.2471915